Tuesday 20 May 2014

Biosciences Seminar Speaker - 22 May 2014

Biosciences Seminar Series - Spring 2014
22 May 2014 - 1pm - Zoology Museum (Wallace 129)

Disease detection in dairy cows through the analysis of individual and social movement behaviour

Dr. Ed Codling

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Radiotracking, telemetry, GPS and biologging techniques have revolutionized the study of animal behavioural and population ecology in the last several decades, as it has become possible to observe the behaviour and survival of animals over long distances, at night and day, under the sea and in the air, etc. Whilst the advantages of these technologies for studying species like polar bears or wandering albatrosses are obvious, one might wonder why one should put similar high-tech biologgers on dairly cows in a barn ... which is what our seminar speaker of this week is doing!  It turns out, though, that there are strong biological and economic reasons for doing that and Dr. Ed Codling, senior lecturer at the Maths Department at the University of Essex, will show us why. For example, it is even not easy to reliably track and record the behaviour of cows within a barn!

Image by Glenn Gorick
Before providing more information on the cow project, a bit more information about our speaker. Ed is a mathematical biologist and is interested in movement and behavioural ecology as well as in the population dynamics and optimal management of fisheries and marine ecosystems. For example, current research focusses on how humans respond to different sources of directional information during crowd evacuations (see here) as well as on multitrophic interactions in the sea (see here) or on zooplankton grazing (see here). Ed might also be considered a front runner in the award for ‘best study of your name’ scientist ever with his publication on Cod fisheries (see here) ...

So, now here why putting collars on cows in a barn is actually important and interesting:

Dairy cow welfare is increasingly a subject of public concern. A major ongoing challenge is the development of methods for automating the detection of welfare problems. Such detection systems should be able to operate as early warning systems and detect the early signs of disease or illness within dairy herds and individual cows. 

Thanks to new technological developments there are potential solutions. Novel local positioning wireless sensors can be deployed over large networks of animals and give positioning information for individuals over long periods of time. It is known that diseases such as lameness in dairy cattle can affect general behaviour, such as how long cows spend lying down. Similarly, social interactions between individual animals, such as how much time they spend close to each other or how closely they synchronise their behaviour, have been suggested as possible measures of animal welfare. However, it is a non-trivial problem to determine and quantify changes in individual and social behaviour and subsequently to use such changes to predict the onset of disease.

Cow with collar (image by Ed Codling)
In this talk, I will explain how we are using automated data collection techniques to record patterns of space use, movement, and social interactions of dairy herds within a confined space (a commercial barn). We are subsequently using a range of techniques and methods borrowed from the ecological literature to analyse and predict the movement, behaviour and welfare status of cows within the herd. 

I will explain how we can use space utilisation methods, hidden Markov models and/or change point analysis to monitor individual behavioural states and highlight abnormal periods of behaviour that may be indicative of reduced welfare. I will also explain how social network analysis techniques will allow us to determine the social hierarchy within the herd and how this may also be used to monitor welfare status. I will illustrate these methods with data from two preliminary trials involving lame v non-lame dairy cows, and a small herd of beef cows.

The project serves as an ideal case study to test and develop new methods for the analysis and modelling of animal movement and behaviour at both the individual and collective level. Our ultimate goal is to develop an on-farm automated 'early warning' system for disease detection. Such a system would be invaluable for improving the welfare and productivity of dairy cows.

Co-authors: Jon Amory, Zoe Barker, Nick Bell, Darren Croft, Holly Hodges and Jorge Vazquez Diosdado

Everyone is most welcome to come and listen!

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